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Understanding the Rise of Obesity: A Genetic Perspective

Exploring how genetic factors and environment shape rising obesity rates.

Liam Wright, N. M. Davies, G. Shireby, D. M. Williams, T. T. Morris, D. Bann

― 6 min read


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Table of Contents

Obesity is a serious issue affecting many people around the world. It contributes to health problems and can lead to early death. The financial cost of dealing with obesity and being overweight is estimated to be over $2 trillion every year. In England, more than one in four adults and one in five children aged 11 years are considered obese. This trend raises concerns for future public health because current generations may experience obesity for longer periods due to patterns in body weight.

Rising Obesity Rates

Obesity rates have dramatically increased in developed countries over the past several decades. This rise has varied from country to country. In England, the rates of obesity in both children and adults have tripled since the mid-1970s. The speed of this increase suggests that our environment plays a crucial role in influencing body weight more than genetic changes do.

Being overweight often comes from consuming more energy (calories) than the body uses. Many changes in society have occurred alongside this obesity epidemic, which may have negatively affected how energy is balanced. While the exact impact of changes in Food consumption and activity levels is debated, several factors have made it easier for people to gain weight. For instance, machines that reduce the need for physical work in homes and workplaces, increased sedentary activities like watching TV and playing video games, and a decline in jobs that require physical labor have all contributed to less activity.

Additionally, food, especially those high in sugar and fat, has become more affordable. People now spend a larger portion of their food budgets on processed foods, and fast-food restaurants have grown in number.

Different Patterns of Obesity

While obesity rates are going up, not everyone is affected equally. The distribution of body weight has become more varied. Levels of underweight individuals have not changed much, but the average body mass index (BMI) has not increased as much as the rise in obesity rates would suggest. This indicates that some people are more vulnerable to becoming obese due to differences that might be genetic. Research shows that Genetics can play a significant role in determining body weight, with studies of twins suggesting hereditary factors can explain about 47-90% of BMI variations.

Certain genetic traits, such as those linked to the FTO gene, have been identified as increasing the risk of obesity. These genetic traits can contribute to behaviors related to food, such as feeling hungrier or feeling full less quickly. This means that in Environments where unhealthy food is cheap and available, people with such traits may find it harder to maintain a healthy weight.

Studies on Gene-Environment Interaction

Some studies have looked into how the influence of genetics on obesity may have changed over time. These studies consider when people were born or the obesity rates during the time they were studied. The findings show that while average BMI has increased, the influence of genetics on BMI has become stronger. However, the overall percentage of BMI variations explained by genetics has remained relatively stable.

One limitation of these studies is that they mostly focus on adults, especially older ones, which might not provide a full picture of the situation in children and teenagers. Genetic effects can differ significantly at various stages of development. Children, for example, typically have less control over their diets and engage in different activities compared to adults.

Previous research has also concentrated on the relationship between genetics and average BMI or obesity, rather than looking closely at how these associations vary across the BMI spectrum.

The British Birth Cohort Studies

The British Birth Cohort Studies, which follow groups of people born in 1946, 1958, 1970, and 2000-2002, provide valuable insight into changing obesity rates. These studies have collected multiple BMI data points over time, covering both pre- and post-obesity epidemic periods. The oldest cohort experienced a relatively stable food environment, while the youngest cohort saw obesity rates soar to 20% by age 11, four times higher than children of the same age two decades earlier.

This study aims to explore how the influence of genetics on childhood and adulthood BMI has changed during the obesity epidemic in the UK. By comparing genetic data tied to BMI from childhood and adulthood, we can see if the effects of genetics have risen over time and if they differ across the BMI distribution.

Data Collection and Methods

Participants from four British birth cohort studies were analyzed, focusing specifically on individuals of White ethnicity born in England, Scotland, or Wales. The cohorts were genotyped at various ages, and BMI data was collected through direct measurements for most ages. Height and weight were measured by interviewers, health visitors, or doctors, while some measurements relied on self-reporting.

For the main analysis, two polygenic indices for adulthood and childhood BMI were created based on large genetic studies. Each index represents the influence of specific genetic variations on BMI.

Key Findings and Results

  1. Average BMI Increases: Each successive cohort showed higher average BMI values as they aged. The increase in variance was primarily due to changes at the higher ends of the BMI distribution, with little change in underweight or median BMI levels.

  2. Genetic Associations: The associations between adult genetic profiles and BMI were consistent across cohorts. However, stronger correlations were noted in the most recently surveyed cohort, with genetic effects on BMI becoming evident from an earlier age. The rise in BMI in the youngest cohort, including children aged 16, showed a greater impact from genetics compared to older cohorts.

  3. Distribution of BMI Effects: The adult genetic profiles were more strongly linked to higher BMI levels in all cohorts. This means that genetics play a larger role in determining obesity among those whose BMI is already high. The largest differences were seen in the youngest cohort.

  4. Heritability Trends: While the influence of the adult genetic profiles on BMI increased as people aged, the overall percentage of BMI variation explained by these genetic factors stayed relatively stable over time. In contrast, childhood genetic influences were stronger during adolescence but dropped off afterwards.

Implications and Considerations

The findings suggest that genetics may influence BMI more significantly in cohorts impacted by the obesity epidemic. The results indicate that genetic markers could not only help in understanding an individual's risk of becoming obese but also highlight the importance of the surrounding environment.

As obesity rates continue to rise, it becomes critical to examine which environmental factors are contributing to these changes in genetic influence on obesity. Exploring the relationship between genetics and behaviors, such as food choices and physical activity, is essential for addressing the obesity crisis.

Conclusion

In summary, obesity is a growing problem with significant health and economic implications. Differences in genetic influences on obesity across generations point to the importance of considering both genetic and environmental factors. Continued research will be essential in identifying how these factors interact and what can be done to mitigate the rising rates of obesity. The insights from longitudinal studies like the British Birth Cohort Studies can guide future efforts to tackle this pressing issue.

Original Source

Title: Genetic Risk for High Body Mass Index Before and Amidst the Obesity Epidemic: Cross-Cohort Analysis of Four British Birth Cohort Studies

Abstract: Obesity is a highly heritable trait, but rising obesity rates over the past five decades suggest environmental change is also of profound importance. We conducted a cross-cohort analysis to examine how associations between genetic risk for high BMI and observed BMI differed in four British birth cohorts born before and amidst the obesity epidemic (1946, 1958, 1970 and [~]2001, respectively; N = 19,379). BMI (kg/m2) was measured at multiple time points between ages 3 and 69 years. We used polygenic indices (PGI) derived from GWAS of adulthood and childhood BMI, respectively, with mixed effects models used to estimate associations with mean BMI and quantile regression used to assess associations across the distribution of BMI. We further used Genomic Relatedness Restricted Maximum Likelihood (GREML) to calculate SNP-heritability (SNP-h2) at each age. Adulthood BMI PGI was associated with BMI in all cohorts and ages but was more strongly associated with BMI in more recently born generations. For example, at age 16y, a 1 SD increase in the adulthood PGI was associated with 0.43 kg/m2 (0.34, 0.51) higher BMI in the 1946c and 0.90 kg/m2 (0.83, 0.97) higher BMI in the 2001c. Cross-cohort differences widened with age and were larger at the upper end of the BMI distribution, indicating disproportionate increases in obesity in more recent generations for those with higher PGIs. Differences were also observed when using the childhood PGI, but there were no clear, consistent differences in SNP-h2. Findings highlight how the environment can modify genetic influence; genetic effects on BMI differed by birth cohort, age, and outcome centile.

Authors: Liam Wright, N. M. Davies, G. Shireby, D. M. Williams, T. T. Morris, D. Bann

Last Update: 2024-10-25 00:00:00

Language: English

Source URL: https://www.medrxiv.org/content/10.1101/2024.10.24.24315860

Source PDF: https://www.medrxiv.org/content/10.1101/2024.10.24.24315860.full.pdf

Licence: https://creativecommons.org/licenses/by/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to medrxiv for use of its open access interoperability.

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